Advancing cancer immunotherapy: from innovative preclinical models to clinical insights

The rapid expansion of cancer immunology and immunotherapy builds upon the success of early immune checkpoint inhibitors (ICI) and chimeric antigen receptor T cells for some cancer types. Many gaps still exist, however, in the scientific knowledge of immune dysfunction in the tumour microenvironment and predicting clinical immunotherapy response to allow more cancer patients to benefit from immunotherapy. The Cancer Immunotherapy Collection within Scientific Reports describes pioneering preclinical and clinical studies addressing these concepts, representing significant insights and breakthroughs in the field.

model, with no overt toxicities observed 8 .This new approach to harness the desired effects of the IL-2 pathway is primed for further testing in various cancers.
In exploration at the intersection of veterinary and human oncology, Dias and collaborators showed the potential of canine lymphoma (cNHL) as a preclinical model for testing anti-CD20 immunotherapies in B-cell malignancies.A novel single-domain antibody that binds to both human and canine CD20 and can be used in therapeutic and diagnostic approaches thus advancing both veterinary and human oncology 9 .
Amengual-Rigo and Guallar presented NetCleave tool, an open-source and retrainable algorithm predicting C-terminal antigen processing for both MHC-I and MHC-II pathways 10 .This enhances our ability to understand and potentially manipulate antigen processing, thereby influencing immune responses 11 .A different tool was presented by Mehdizadeh and colleagues for simulating myeloid-derived suppressor cells (MDSC) depletion in a mouse model of aggressive tumours.The computational simulations suggest that vaccination with a small number of tumour cells in combination with MDSC depletion elicits an effective anti-tumour immune response and tumour dormancy 12 .
The studies using clinical data featured in this Collection exemplify efforts to eventually translate research on biomarkers and mechanisms of immunotherapy responders or non-responders in clinical trials or clinical care, thus offering insights into improving cancer treatment strategies.Kauffmann-Guerrero and collaborators investigated the potential of inflammation and cytokine profiles as biomarkers for non-small-cell lung cancer patients receiving ICI and revealed inflammation markers that dictate response to ICI treatment 13 .This study highlights the limitations of relying solely on PD-L1 expression and emphasizes the importance of inflammatory biomarkers for predicting treatment response.The analysis of immune changes in multiple myeloma patients receiving ICI and the immunomodulator pomalidomide in Phase 1b trial (NCT02616640) reported by Newhall and collaborators emphasized transcriptome changes consistent with favourable immunomodulation 14 , but also the risk of increasing autoimmune response and adverse events, as evidenced by other ongoing trials.In a parallel exploration, Mendoza and co-workers detailed patients' symptom burden in early-phase trials for rare solid tumours treated with immunotherapy.This prospective longitudinal study showed the distribution of high immunotherapy-specific symptom burden 15 , and the results may help inform the planning of future symptom interventional clinical trials for patients receiving ICI.
Continuing the quest for the efficacy of combination therapies, the real-world outcomes for metastatic nonsmall cell lung cancer patients treated with first-line Pembrolizumab plus chemotherapy were compared by Velcheti and collaborators to the clinical trial that led to the approval of this combined immunotherapy.This study provided substantial evidence of outcomes from combination therapy in a more heterogeneous patient cohort and clinical care setting 16 .In a departure from traditional biomarkers, Naing and collaborators brought us the associations between microbiome composition and fatigue in advanced cancer patients.The authors revealed microbiome-associated bacteria negatively and positively associated with fatigue severity 17 , uncovering potential insights into patient well-being and treatment outcomes.
In searching for novel immune molecular classification, Yu and colleagues applied a non-negative matrix factorization algorithm and subdivided colorectal cancer into immune classes based on the immunocyte infiltration and enrichment of immune response-associated signatures.The immune-suppressed subclass had the worst overall prognosis, while patients within the immune-activated subclass showed better prognosis and response to anti-PD-1 therapy 18 .Finally, from a different perspective, Krishnan and colleagues proposed the GaWRDenMap framework utilizing geographically weighted regression and a density function-based classification model that discriminates between chronic pancreatitis, pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasm at both the subject-and image-levels 19 .It could also reasonably discriminate between PDAC.These results indicate a potential difference in the spatial arrangement of epithelial and immune cells in the pancreas can have diagnostic significance.

Conclusions
This Advancing Cancer Immunotherapy Collection in Scientific Reports embodies diverse studies pushing the boundaries of cancer immunology and treatment.These papers deepen our understanding of immunotherapeutic mechanisms and present novel strategies and perspectives to advance cancer treatment outcomes.The research findings within this Collection include innovations and highlight the power of collaborations across disciplines, paving the way to expanding the application of cancer immunotherapy so more cancer patients will benefit.